Shared Data and Resources
Pacific Northwest National Laboratory (PNNL) offers resources, developed as part of our systems biology program, to facilitate research conducted by members of the systems biology community. Our single-chain antibody library is available to scientists whose research or teaching is U.S. Government related. We also provide free bioinformatic tools for all researchers to download.
Single-Chain Antibody Library
Contact: Cheryl Baird
PNNL researchers cloned a library of 109 human antibody scFv fragments expressed on the surface of yeast cells using a platform designed by collaborator Dane Wittrup of the Massachusetts Institute of Technology. This yeast library is the first nonimmune antibody library to be cloned, expressed, and screened on the yeast surface, and it is the largest reported yeast expression library of any kind.
Learn more about the single-chain antibody library.
Proteomics Research Resource for Integrative Biology Software
Tools developed as part of the Resource enhance LC-MS data analysis.
The Proteomics Research Resource for Integrative Biology is a national user facility established and funded by the National Center for Research Resources component of the National Institutes of Health. The Resource is housed in the Environmental Molecular Sciences Laboratory (EMSL) at PNNL.
As part of the Resource, many sophisticated Software and Tools for proteomics have been developed and are available for download. Software and tools developed as part of the Resource manage and process high-throughput proteomic data, interpret mass spectra, visualize and characterize features detected during liquid chromatography-mass spectrometry (LC-MS) analysis, as well as calculate molecular weights of chemical formulas and amino acids.
ProMAT
ProMAT was spotlighted by Science magazine's NetWatch in June 2006.
Contact: Amanda White
The Protein Microarry Analysis Tool (ProMAT) was designed for use with enzyme-linked immunosorbent assays to analyze protein microarray data. ProMat yields protein concentration values and statistically significant information about data quality in HTML format for researchers to view and share data easily.
ProMAT was featured in Science magazine's NetWatch in June 2006, and an article about ProMAT was published in the May 2006 edition of Bioinformatics.
Learn more about ProMAT, and download the software for free.
Bioinformatics Resource Manager
Contact: Katrina Waters
Bioinformatics Resource Manager (BRM) seamlessly connects researchers; data sources, including data in private, publicly available, and custom in-house formats; and commercial and private bioinformatic tools. BRM allows biologists to use efficiently analytic techniques that are otherwise costly, time-consuming, require expertise in bioinformatics and statistics, and require knowledge of data sources.
An article on BRM was featured in the March 2006 issue of Scientific Computing.
Learn more about BRM, and download the software for free.
Collective Analysis of Biological Interaction Networks
CABIN uses interactive visual interfaces.
Contact: Mudita Singhal
The Collective Analysis of Biological Interaction Networks (CABIN) was developed as a plugin to Cytoscape, which is an open source network visualization and analysis tool. CABIN promotes analytical reasoning for integrating evidence of interaction data from multiple sources by the use of interactive visual interfaces. It facilitates integration and analysis of evidence from multiple prediction and experimental sources, such as Gene Neighborhood-GN, Gene Cluster-GC, Phylogenetic Profiles-PP, Rosetta Stones-RS, BIND, and DIP. Multiple coordinated views within CABIN foster exploratory data analysis by users, accommodating expert domain knowledge.
Learn more about CABIN, and download the software for free.
Support Vector Machine (SVM)-based tool to detect Homology Using Semi-supervised iTerative LEarning (SVM-HUSTLE)
Contact: Anuj Shah
The Support Vector Machine (SVM)-based tool to detect Homology Using Semi-supervised iTerative LEarning (SVM-HUSTLE) identifies significantly more remote homologs than current state-of-the-art sequence or cluster-based methods.
Learn more about SVM-Hustle.